1. Field of the Invention
The present invention relates to a Wireless Sensor Network (WSN). More particularly, the present invention relates to techniques for a self-organizing activity-diffusion-based WSN.
2. Description of the Related Art
Recently, the concept of a Wireless Sensor Network (WSN) has received considerable attention. A WSN typically includes a collection of low-power transceivers (henceforth referred to as sensor nodes) each having some type of sensor function for one or more properties of an environment in which they are placed. The term “environment” here has a very broad meaning and could include any object or geographical area. Likewise, the range of properties which might be sensed is wide, and includes any property that may be indirectly or directly sensed, or determined based on the sensing of one or more other properties.
Each sensor node is capable of transmitting sensor data, usually as discrete packets, to any other devices in its vicinity, usually to another sensor node. By relaying data from one sensor node to another, the data can be directed to a so-called sink node or base station. The sensor node may be fixed or mobile, and the sink nodes may be fixed or mobile. Although the precise communication standard used by the sensor nodes of a WSN is not important, one suitable standard is Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard, an implementation of which is referred to as ZigBee.
Depending upon the capabilities of the sink node, the data can be forwarded from the sink node directly or indirectly to some form of outside entity, typically via another network such as a mobile telephone network or the Internet. Where the sink node is able to communicate with another network it may also be referred to as a gateway.
In some implementations, the terms sink node, base station and gateway denote the same thing. In other implementations, the terms sink node, base station and gateway denote distinct functions, in which case, the sink node will communicate the gathered data to a separate base station and/or gateway for further transmission, possibly after some type of aggregation or other processing.
Moreover, in some implementations, the sensor nodes (or a subset thereof) are also capable of acting as the sink node. Multiple sink nodes, and multiple gateways, may be present in a WSN, but, for simplicity, a single sink node is assumed in the following description.
In the present disclosure, the terms “sink node” and “base station” are used synonymously to denote any type of data-gathering entity in a WSN, whether or not it also acts as a gateway.
The WSN differs from a wireless mesh network and an ad hoc network. Typically, the sensor nodes are unattended, have a low computational ability, and are reliant on battery power. Thus, power consumption of the sensor nodes is a major consideration and the transmission of data is typically the most power-hungry function of a sensor node. Therefore, the sensor nodes operate with severe energy constraints. However, the sensor nodes may be Radio Frequency IDentification (RFID)-based devices, which might not be reliant on battery power. Nevertheless, since the available transmission power of such devices is very low, similar considerations apply.
One technique employed to conserve battery power is to deactivate sensor nodes that are not currently engaged in sensing or communication (including relaying). Thus, sensor nodes may alternate between active and inactive states, for example, in response to the presence or absence of a sensed property or incoming data. In this way, the useful lifetime of the sensor can be prolonged.
Another technique employed to conserve battery power is to have sensor nodes only communicate with their nearest neighbors. However, by limiting the communication of sensor nodes to only their nearest neighbors, multi-hop techniques need to be used to enable sensor data to reach the sink node by several different routes. However, in employing this technique, the sensor nodes transmit data in all directions indiscriminately without knowing or caring which other nodes receive it. Accordingly, a WSN suffers from the transmission of redundant data.
Data aggregation has been put forward as a useful solution to address the limited energy constraints and redundant data. Data aggregation exploits the fact that a sensor node consumes less energy for data processing than for communication. Also, it minimizes the number of transmissions and thereby conserves energy. Instead of transmitting the packets of each individual sensor node separately, each sensor node first combines the incoming data from different sources en-route and then forwards the aggregated data to the next node when its aggregation interval is reached.
In a WSN, the interplay between topology formation and data aggregation is very important. Data aggregation schemes of the related art separate the topology formation and data aggregation from each other. In other words, a topology is formed first and then data aggregation is performed based on the topology. However, the pre-constructed topologies are not always the best structures for efficient data aggregation. An aggregation topology according to the related art will be discussed below with reference to FIG. 1.
FIG. 1 illustrates an aggregation topology according to the related art.
Referring to FIG. 1, the communication paths of sensor data collected by sensor nodes N1, N2 and N3 and communicated to the sink node S1 are shown. Here, the communication paths are formed based on the shortest paths for the data to travel between the sensor nodes N1, N2 and N3 and the sink node S1. The aggregation topology employed here is referred to as a shortest path tree. By following the shortest path, the packets from sensor nodes N1, N2 and N3 are routed separately to the sink node S1 and are not able to be aggregated en-route. In this case, this topology does not yield the most efficient result. Here, it would have been more efficient to perform data-aggregation and then have the aggregated data communicated to the sink node S1.
Therefore, a need exists for a data-aggregation driven topology for efficient data aggregation.